A Clinical Model for the Early Diagnosis of Acute Pancreatitis in the Emergency Department. Issue 7 (August 2018)

• Record Type: Journal Article
• Authors: Jin, David X.; Lacson, Ronilda; Cochon, Laila R.; Alper, Emily C.; McNabb-Baltar, Julia; Banks, Peter A.; Khorasani, Ramin
• Is Part Of: Pancreas. Volume 47:Issue 7(2018)
• Publication Date: 2018-08
• Subjects: acute pancreatitis -- computed tomography -- diagnostic model -- lipase -- magnetic resonance imaging; Pancreas -- Diseases -- Periodicals; Pancreas -- Periodicals; Neuroendocrine tumors -- Periodicals; 616.37005
• DOI: 10.1097/MPA.0000000000001102
• Languages: English
• ISSNs: 0885-3177

Abstract

Abstract : Objective: This study aimed to develop a diagnostic model that predicts acute pancreatitis (AP) risk before imaging. Methods: Emergency department patients with serum lipase elevated to 3 times the upper limit of normal or greater were identified retrospectively (September 1, 2013–August 31, 2015). An AP diagnosis was established by expert review of full hospitalization records. Candidate predictors included demographic and clinical characteristics at presentation. Using a derivation set, a multivariable logistic regression model and corresponding point-based scoring system was developed to predict AP. Discrimination accuracy and calibration were assessed in a separate validation set. Results: In 319 eligible patients, 182 (57%) had AP. The final model (area under curve, 0.92) included 8 predictors: number of prior AP episodes; history of cholelithiasis; no abdominal surgery (prior 2 months); time elapsed from symptom onset; pain localized to epigastrium, of progressively worsening severity, and severity level at presentation; and extent of lipase elevation. At a diagnostic risk threshold of 8 points or higher (≥99%), the model identified AP with a sensitivity of 45%, and a specificity and a positive predictive value of 100%. Conclusions: In emergency department patients with lipase elevated to 3 times the upper limit of normal or greater, this model helps identify AP risk before imaging. Prospective validation studies are needed to confirm diagnostic accuracy. Abstract : Supplemental digital content is available in the text.